Evaluating the effects of bilingual traffic signs on driver performance and safety

Variable Message Signs (VMS) can provide immediate and relevant information to road users and bilingual VMS can provide great flexibility in countries where a significant proportion of the population speak an alternative language to the majority. The study reported here evaluates the effect of various bilingual VMS configurations on driver behaviour and safety. The aim of the study was to determine whether or not the visual distraction associated with bilingual VMS signs of different configurations (length, complexity) impacted on driving performance. A driving simulator was used to allow full control over the scenarios, road environment and sign configuration and both longitudinal and lateral driver performance was assessed. Drivers were able to read one and two-line monolingual signs and two-line bilingual signs without disruption to their driving behaviour. However, drivers significantly reduced their speed in order to read four-line monolingual and four-line bilingual signs, accompanied by an increase in headway to the vehicle in front. This implies that drivers are possibly reading the irrelevant text on the bilingual sign and various methods for reducing this effect are discussed

Towards Agent-Based Traffic Simulation Using Live Data from Sensors for Smart Cities

The Smart City and Internet-of-Things revolutions enable the collection of various types of data in real-time through sensors. This data can be used to improve the decision tools and simulations used by city planners. This paper presents a new framework for real-time traffic simulation integrating an agent-based methodology with live CCTV and other sensor data while respecting the privacy regulations. The framework simulates traffic flows of pedestrians, vehicles and bicycles and their interactions. The approach has been applied in Liverpool (NSW, Australia) showing promising preliminary results and can easily ingest additional sensor data, e.g. air quality

Backbone and ILV methyl resonance assignments of E. coli thymidylate synthase bound to cofactor and a nucleotide analogue

Thymidylate synthase (TSase) is a 62 kDa homodimeric enzyme required for de novo synthesis of thymidine monophosphate (dTMP) in most organisms. This makes the enzyme an excellent target for anticancer and microbial antibiotic drugs. In addition, TSase has been shown to exhibit negative cooperativity and half-the-sites reactivity. For these collective reasons, TSase is widely studied, and much is known about its kinetics and structure as it progresses through a multi-step catalytic cycle. Recently, nuclear magnetic resonance (NMR) spin relaxation has been instrumental in demonstrating the critical role of dynamics in enzyme function in small model systems. These studies raise questions about how dynamics affect function in larger enzymes with more complex reaction coordinates. TSase is an ideal candidate given its size, oligomeric state, cooperativity, and status as a drug target. Here, as a pre-requisite to spin relaxation studies, we present the backbone and ILV methyl resonance assignments of TSase from Escherichia coli bound to a substrate analogue and cofactor

Towards Agent-Based Traffic Simulation Using Live Data from Sensors for Smart Cities

The Smart City and Internet-of-Things revolutions enable the collection of various types of data in real-time through sensors. This data can be used to improve the decision tools and simulations used by city planners. This paper presents a new framework for real-time traffic simulation integrating an agent-based methodology with live CCTV and other sensor data while respecting the privacy regulations. The framework simulates traffic flows of pedestrians, vehicles and bicycles and their interactions. The approach has been applied in Liverpool (NSW, Australia) showing promising preliminary results and can easily ingest additional sensor data, e.g. air quality